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[null,null,"Titolo",null,"Future data and security engineering : big data, security and privacy, smart city and Industry 4.0 applications : 8th international conference, FDSE 2021, virtual event, November 24-26, 2021, proceedings / / edited by Tran Khanh Dang [and three others]"]
[null,null,"Pubbl/distr/stampa",null,"Gateway East, Singapore : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"981-16-8062-0"]
[null,null,"Descrizione fisica",null,"1 online resource (502 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science ; ; v.1500"]
[null,null,"Disciplina",null,"005.8"]
[null,null,"Soggetti",null,"Data encryption (Computer science)"]
[{"$nulls":4},"Computer security"]
[{"$nulls":4},"Data mining"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- Big Data Analytics and Distributed Systems -- Document Representation with Representative Sets and Document Similarity at Sentence Level Using Maximum Matching in Bipartite Graph -- 1 Introduction -- 2 Related Work -- 3 Proposed Methods -- 3.1 Document Centroid Vector Method -- 3.2 Single Representative Set Method -- 3.3 Maximum-Matching with Minimum-Cost in Bipartite Graph -- 3.4 Multi Representative Sets -- 4 Experiments with Vietnamese Dataset and Online Utilities for Vietnamese Document Analysis -- 4.1 Dataset -- 4.2 Document Representation with Representative Sets: Experiments and Online Utility -- 4.3 Topic Relevance Experiment and Online Utility -- 4.4 Sentence Matching Experiment and Online Utility -- 5 Conclusion -- References -- A Hybrid Approach Using Decision Tree and Multiple Linear Regression for Predicting Students' Performance -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Feature Selection -- 3.3 Decision Tree -- 3.4 Model Evaluation -- 4 Results -- 4.1 Feature Selection -- 4.2 Decision Tree and Multiple Linear Regression Model -- 4.3 Decision Support System -- 5 Conclusions -- References -- Human Mobility Prediction Using k-Latest Check-ins -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Data Description -- 3.2 K-Latest Check-ins (kLC) -- 4 Results -- 4.1 "]
[{"$nulls":4},"Settings -- 4.2 Performance Metric -- 4.3 Experiment Results -- 5 Conclusion -- References -- Hospital Revenue Forecast Using Multivariate and Univariate Long Short-Term Memories -- 1 Introduction -- 2 Related Work -- 3 The Proposed Method for Hospital Revenue Forecast -- 3.1 Data Description -- 3.2 Features Importance -- 3.3 Neural Networks Setting -- 4 Experimental Results -- 4.1 Metrics for Evaluation -- 4.2 Hospital Revenue Forecasting -- 5 Conclusion -- References."]
[{"$nulls":4},"Using Some Machine Learning Methods for Time Series Forecasting Regarding Gold Prices -- 1 Introduction -- 2 Related Works -- 3 Some Research Models -- 3.1 The ARIMA Model -- 3.2 The SARIMA Model -- 3.3 Recurrent Fuzzy Neural Network -- 3.4 The ARIMA-LSTM Combined Model Based on MA Filter -- 4 Experimental Results and Assessment -- 4.1 The Results of Using the ARIMA Model -- 4.2 The Results of Using the SARIMA Model -- 4.3 The Results of Using the Recurrent Fuzzy Neural Network -- 4.4 The Results of Using the ARIMA - LSTM Combined Model -- 4.5 Evaluation of Experimental Results -- 5 Conclusion -- References -- Security and Privacy Engineering -- Improving ModSecurity WAF Using a Structured-Language Classifier -- 1 Introduction -- 2 Background and Related Works -- 2.1 Background -- 2.2 Related Works -- 3 Proposed Approach -- 3.1 System Analysis -- 3.2 Architecture -- 4 System Implementation and Datasets -- 4.1 System Implementation -- 4.2 Datasets -- 5 Experiments and Evaluation -- 5.1 Request Categorizer -- 5.2 End-to-End Test -- 6 Discussion -- 7 Conclusion -- References -- Security Issues in Android Application Development and Plug-in for Android Studio to Support Secure Programming -- 1 Introduction -- 2 Related Work -- 2.1 Security Issues in Android Applications -- 2.2 Android Secure Coding Methodologies and Tools -- 3 Security Issues in Android Applications -- 3.1 Security in Cryptography Implementation -- 3.2 Security in Client-Side and Click-Jacking Prevention -- 3.3 Security in Communication Between Application and Server -- 3.4 Security in Android Components -- 3.5 Protect Data Stored on Mobile Phones -- 3.6 Secure Coding with Logs and Debug Information -- 4 Secure Coding Plugin for Android Studio -- 4.1 Android Lint -- 4.2 Proposed Architecture for Extending Android Lint's Detection and Reporting System."]
[{"$nulls":4},"4.3 9Fix: Android Studio Secure Coding Plug-in -- 4.4 Example of Use -- 4.5 Rules Customization for a Specific Project -- 4.6 Security Checklist -- 5 Experiment Results -- 5.1 Performance -- 5.2 User Experience -- 6 Conclusion -- References -- On Using Cryptographic Technologies in Privacy Protection of Online Conferencing Systems -- 1 Introduction -- 2 Related Work -- 3 Material and Methodologies -- 3.1 Time-Based One-Time Password (TOTP) -- 3.2 InsertableStream -- 4 System Design and Integration -- 4.1 Online Conference Application -- 4.2 Authentication Application -- 4.3 System Integration -- 5 Experiment and Results -- 5.1 Experimental Specifications -- 5.2 Experimental Results -- 5.3 Quality of Service Evaluation -- 5.4 Discussion -- 6 Conclusion and Future Work -- References -- A Survey of Machine Learning Techniques for IoT Security -- 1 Introduction -- 2 IoT Security Risks -- 3 Current IoT Security Research Trends -- 3.1 Existing IoT Security Solutions Based on Machine Learning -- 3.2 ML-Based IoT Security Classification -- 3.3 Limitations in Applied Machine Learning in IoT System -- 4 Evaluation on ML-Based Techniques for IoT Security -- 5 Conclusions -- References -- Industry 4.0 and Smart City: Data Analytics and Security -- A Prediction-Based Cache Replacement Policy for Flash Storage -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Cache Structure and Policies -- 3.2 Future "]
[{"$nulls":4},"Reference Prediction -- 4 Performance Evaluation -- 4.1 Experiment Setting -- 4.2 Experiment Result -- 5 Conclusion -- References -- A Deep Learning-Based Method for Image Tampering Detection -- 1 Introduction -- 2 Related Works -- 3 Problem Statement -- 4 Proposed Method -- 4.1 YOLO Algorithm [1] -- 4.2 A Model of Tampering Detection -- 5 Simulation Results -- 6 Conclusions -- References."]
[{"$nulls":4},"Building a Vietnamese Dataset for Natural Language Inference Models -- 1 Introduction -- 2 The Constructing Method -- 2.1 NLI Sample Generation -- 2.2 Entailment Pair Collection -- 3 Building Vietnamese NLI Dataset -- 3.1 Contradiction Creation Guidelines -- 3.2 Building Steps -- 3.3 Building Results -- 4 Experiments -- 4.1 Experiment Settings -- 4.2 Experiment Results -- 5 Conclusion and Future Works -- References -- One-Class Classification with Noise-Based Data Augmentation for Industrial Anomaly Detection -- 1 Introduction -- 2 Related Works -- 3 Method -- 4 Experiments -- 5 Concluding Remarks -- References -- Features Selection in Microscopic Printing Analysis for Source Printer Identification with Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 4 Experiments -- 5 Conclusion -- References -- Forecasting and Analyzing the Risk of Dropping Out of High School Students in Ca Mau Province -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Data Collection -- 3.2 Data Pre-processing -- 3.3 Using Machine Learning Models -- 3.4 Extraction of Essential Features -- 4 Experimental Result -- 4.1 Machine Learning Model Evaluation -- 4.2 Experimental Result -- 4.3 Features Extraction for Analyzing Factors Affecting Students' Dropout -- 5 Conclusion and Future Work -- References -- Personalized Student Performance Prediction Using Multivariate Long Short-Term Memory -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Datasets for the Experiments -- 3.2 Data Pre-processing -- 3.3 Learning Models for Student Performance -- 4 Evaluation of Results -- 4.1 Evaluation Method -- 4.2 Experimental Results -- 5 Conclusion -- References -- Estimating the Traffic Density from Traffic Cameras -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Faster RCNN Structure -- 3.2 API Send SMS - Nexmo."]
[{"$nulls":4},"3.3 Emailing API - SendGrid -- 3.4 Evaluation Methods -- 4 Experiment Results and Discussion -- 4.1 The datasets -- 4.2 Experiment Results -- 5 Conclusion and Future Work -- References -- Air Pollution Forecasting Using Regression Models and LSTM Deep Learning Models for Vietnam -- 1 Introduction -- 2 Related Works -- 3 Study Area and Methodology -- 3.1 Dataset Description -- 3.2 Dataset Preprocessing -- 3.3 Time Series Modeling -- 4 Model Description -- 4.1 LSTM and BLSTM -- 4.2 Performance Criteria -- 4.3 Parameter Optimization -- 5 Result -- 6 Conclusion -- References -- Proposing Recommendation System Using Bag of Word and Multi-label Support Vector Machine Classification -- 1 Introduction -- 2 Related Work -- 3 System Design -- 3.1 Overview of Proposal System -- 3.2 Building Model -- 3.3 Training Process -- 4 Simulation and Result -- 4.1 Setup -- 4.2 Result -- 4.3 Deploying on Website -- 5 Conclusion -- References -- Blockchain and Access Control -- IU-SmartCert: A Blockchain-Based System for Academic Credentials with Selective Disclosure -- 1 Introduction -- 2 Related Work -- 3 Proposed Solution -- 3.1 Defining a Credential Schema -- 3.2 Issuing Credentials -- 3.3 Generating Receipts -- 3.4 Exchanging Credentials -- 3.5 Revoking Credentials -- 3.6 Verifying a Credential -- 4 Security Analysis -- 4.1 Authenticity and Protection Against Spoofing Identity -- 4.2 Integrity of Users's Credentials (Protection Against Tampering) -- 4.3 Originality and Repudiation -- 4.4 Protection Against Information Disclosure -- "]
[{"$nulls":4},"4.5 Denial of Service -- 4.6 Elevation of Privilege -- 5 Proof of Concept and Experimental Results -- 5.1 Implementation -- 5.2 Cost of Transactions -- 6 Discussion -- 7 Conclusion -- References -- An Approach for Project Management System Based on Blockchain -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Blockchain."]
[{"$nulls":4},"3.2 Smart Contract."]